Grover, Rhythm, Sharma, Aditi, Delcourt, Théo and Kundu, Debasis (2022) Computationally Efficient Algorithm for Frequency Estimation of a Two-Dimensional Sinusoidal Model. Circuits, Systems, and Signal Processing, 41 (1). pp. 346-371. ISSN 0278-081X
Full text not available from this repository.Abstract
In this paper, we propose a computationally faster yet conceptually simple methodology to estimate the parameters of a two-dimensional (2-D) sinusoidal model in the presence of additive white noise. We develop the large sample properties like consistency and asymptotic normality of these low-complexity estimators, and they are observed to be theoretically as efficient as the ordinary least squares estimators. To assess the numerical performance, we conduct extensive simulation studies. The results indicate that the proposed estimators can successfully replace the least squares estimators for sample size as small as 20 × 20 and for signal-to-noise ratio (SNR) as small as 12 dB.
| Item Type: | Article |
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| Additional Information: | Funding Information: The authors would like to thank four anonymous reviewers for their constructive suggestions. Part of the work of the fourth author has been supported by a grant from the Science and Engineering Research Board, Department of Science and Technology, Government of India. Publisher Copyright: © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. |
| Divisions: | Economics |
| Date Deposited: | 07 May 2024 14:03 |
| Last Modified: | 10 Aug 2024 00:15 |
| URI: | http://eprints.lse.ac.uk/id/eprint/122962 |
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